Papers with fully unsupervised learning method

1 papers
Universal Sentence Representation Learning with Conditional Masked Language Model (2021.emnlp-main)

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Challenge: Existing methods to learn sentence representations on unlabeled corpora are difficult and expensive to obtain, making it hard to cover many domains and languages.
Approach: They propose a method to train sentence representations on large unlabeled corpora by conditioning on the encoded vectors of adjacent sentences.
Outcome: The proposed method outperforms existing models on SentEval and can be extended to a broad range of languages and domains.

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